[leftmargin=*]
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LSTM: LSTM(128) \(\rightarrow \)  FC(128) \(\rightarrow \)  ReLU \(\rightarrow \)  \(\Vert \)  \(\rightarrow \)  cross-entropy. This is the configuration in the code we originally released and then corrected.
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LSTM1: LSTM(128) \(\rightarrow \)  FC(128) \(\rightarrow \)  \(\Vert \)  \(\rightarrow \)  cross-entropy
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LSTM2: LSTM(128) \(\rightarrow \)  FC(40) \(\rightarrow \)  \(\Vert \)  \(\rightarrow \)  cross-entropy
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LSTM3: LSTM(128) \(\rightarrow \)  FC(40) \(\rightarrow \)  ReLU \(\rightarrow \)  \(\Vert \)  \(\rightarrow \)  cross-entropy
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LSTM4: LSTM(128) \(\rightarrow \)  FC(128) \(\rightarrow \)  ReLU \(\rightarrow \)  \(\Vert \)  \(\rightarrow \)  FC(40) \(\rightarrow \)  cross-entropy. This is the correct configuration as clearly reported in [1]}. Indeed, the other three configurations just encode class labels, while this one projects the input EEG data into a new manifold where data can be classified.

